CvMcens: Cramér-von Mises test for complete and right-censored data

In GofCens: Goodness-of-Fit Methods for Complete and Right-Censored Data

Cramér-von Mises test for complete and right-censored data

Description

CvMcens computes the Cramér-von Mises statistic and p-value for complete and right-censored data against eight possible distributions.

Usage

CvMcens(times, cens = rep(1, length(times)),
        distr = c("exponential", "gumbel", "weibull", "normal",
                  "lognormal", "logistic", "loglogistic", "beta"),
        betaLimits = c(0, 1), igumb = c(10, 10), degs = 3, BS = 999,
        params0 = list(shape = NULL, shape2 = NULL,
                       location = NULL, scale = NULL),
        prnt = TRUE, outp = "list", tol = 1e-04)

Arguments

times	Numeric vector of times until the event of interest.
cens	Status indicator (1, exact time; 0, right-censored time). If not provided, all times are assumed to be exact.
distr	A string specifying the name of the distribution to be studied. The possible distributions are the exponential ("exponential"), the Weibull ("weibull"), the Gumbel ("gumbel"), the normal ("normal"), the lognormal ("lognormal"), the logistic ("logistic"), the loglogistic ("loglogistic"), and the beta ("beta") distribution.
betaLimits	Two-components vector with the lower and upper bounds of the Beta distribution. This argument is only required, if the beta distribution is considered.
igumb	Two-components vector with the initial values for the estimation of the Gumbel distribution parameters.
degs	Integer indicating the number of decimal places of the numeric results of the output.
BS	Number of bootstrap samples.
params0	List specifying the parameters of the theoretical distribution. By default, parameters are set to NULL and estimated with the maximum likelihood method. This argument is only considered, if all parameters of the studied distribution are specified.
outp	Indicator of how the output will be displayed. The possible formats are list and table.
prnt	Logical to indicate if the estimations of the Anderson-Darling statistic and p-value should be printed. Default is TRUE.
tol	Precision of survival times.

Details

Koziol and Green (1976) proposed a Cramér-von Mises statistic for randomly censored data. This function reproduces this test for a given survival data and a theorical distribution. In presence of ties, different authors provide slightly different definitions of the product-limit estimator, what might provide different values of the test statistic.

The parameter estimation is acomplished with the fitdistcens function of the fitdistrplus package.

To avoid long computation times due to bootstrapping, an alternative with complete data is the function cvm.test of the goftest package.

The precision of the survival times is important mainly in the data generation step of the bootstrap samples.

Value

If prnt = TRUE, a list containing the following components:

Distribution	Null distribution.
Null hypothesis	Parameters under the null hypothesis (if params0 is provided).
CvM	Value of Cramér-von Mises statistic.
p-value	Estimated p-value.
Parameters	List with the maximum likelihood estimates of the parameters of the distribution under study.

The list is also returned invisibly.

Warning

If the amount of data is large, the execution time of the function can be elevated. The parameter BS can limit the number of random censored samples generated and reduce the execution time.

Author(s)

K. Langohr, M. Besalú, M. Francisco, G. Gómez.

References

J. A. Koziol and S. B. Green. A Cramér-von Mises statistic for randomly censored data. In: Biometrika, 63 (3) (1976), 465-474.

A. N. Pettitt and M. A. Stephens. Modified Cramér-von Mises statistics for censored data. In: Biometrika, 63 (2) (1976), 291-298.

See Also

Function cvm.test (Package goftest) for complete data and gofcens for statistics and p-value of Kolmogorov-Smirnov, Cramér von-Mises and Anderson-Darling together for right-censored data.

Examples

# Complete data
set.seed(123)
CvMcens(times = rweibull(100, 12, scale = 4), distr = "weibull",
        BS = 199)

## Not run: 
# Censored data
library(survival)
colonsamp <- colon[sample(nrow(colon), 100), ]
CvMcens(colonsamp$time, colonsamp$status, distr = "normal")

## End(Not run)

GofCens documentation built on May 29, 2024, 2:47 a.m.